hightail | automatic tester for programming contests | Learning library
kandi X-RAY | hightail Summary
kandi X-RAY | hightail Summary
Hightail is an automatic tester for programming contests such as CodeForces rounds. It will parse the problem statement, extract sample test cases (inputs and outputs) from it, and verify the correctness of your program against them. It is built to provide maximum automation and to relieve the contestant as much as possible.
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Top functions reviewed by kandi - BETA
- Initialize the form components
- Adds a list of problems to the tabbed pane
- Display confirmation and close the connection
- Called when newContistigation is pressed
- Make keyboard shortcuts
- Display test tests
- Saves the tests
- Initialize the components
- Open the containing directory button
- Main entry point
- Get a match parser for the specified URL
- Make shortcuts for the tab
- Starts the HTTP server
- Make shortcuts to confirm buttons
- Returns a string representation of the result
- Loads properties from the properties file
- Runs the file
- Adds the popup menu to the tabbed pane
- Sets the shortcut shortcuts
- Handles a request
- Get the renderer for this table
- Parses the URL and creates a problem
- Calculates the difference between two outputs
- Parses the problem
- Parse the problem from the URL
- Notifies the end of the test
hightail Key Features
hightail Examples and Code Snippets
Community Discussions
Trending Discussions on hightail
QUESTION
ANSWER
Answered 2022-Jan-30 at 10:05Try
QUESTION
Newbie here, but I've tried to do my due diligence before posting. Apologies for any unintentional faux pas.
I'm acquiring data from an oscilloscope in the form of a Voltage vs. Time series. The time bins are 0.8nano seconds wide. I run multiple 'data capture' cycles. A single capture will have a fixed number of samples, and between 5 to 15 gaussian peaks with the exact number of peaks being unknown. The gaussian peaks have a relatively constrained FWHM (between 2 and 3 nanoseconds), a varying peak height, and a random arrival time (i.e centroid position is not periodic).
I've been using Python to fit gaussians to this data and have had some success using the scipy.optimise library and also with the astropy library. Code using scipy.optimise is included below. I can fit multiple gaussians but a key step in my code is providing a "guess" for number of peaks, and for each peak an estimate of the centroid positions, peak height, and peak widths. Is there a way to generalise this code and not have to provide a 'guess'? If I relax the conditions in the 'guess' the fits lose quality. I know that the peaks will be gaussians with a well constrained width, but would like to generalise the code to fit peak centroids and peak heights in any given data capture.
...ANSWER
Answered 2021-Oct-29 at 08:05My idea is that we compare the value of the curve with its average value.
The multiplier
variable means how many times the value must be greater than the average in order for us to understand that this is one of the peaks. The first point for a peak exceeding this value is considered the starting point for approximating the average value of this peak.
I also replaced the lists with arrays for x and y.
QUESTION
I am quite new to python so please bear with me.
My code so far is below:
...ANSWER
Answered 2020-Jul-09 at 13:16Graph created. The cause of the error is an extra space at the end of the column name in the provided CSV file. The code fixes that. If you fixed the column names in the original data, you should also fix the code.
QUESTION
I am quite new to python so please bear with me.
My code is below:
...ANSWER
Answered 2020-Jul-09 at 05:57The best way to draw multiple graphs is to use plt.subplots()
. It's easy. The data is created appropriately.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install hightail
Download and install NetBeans (also JDK if you don't have it; there's a bundled version available). I have used NetBeans 8.0 (and Windows) for this tutorial.
While it's installing, sign up on Github if you don't have an account. Go to https://github.com/dj3500/hightail and fork the repository (using the Fork button).
Fire up NetBeans and select Team -> Git -> Clone; Repository URL: https://github.com/YOURUSERNAME/hightail.git/, also enter your Github username and password and select Save password; Next, Next, Finish.
If it says "Hightail project was cloned. Do you want to open the project?", select Open Project. If it doesn't, or says something else (like prompting you to "Create a project"), cancel and open the imported project yourself (File -> Open Project).
Change stuff, test, build, run, etc.
Once you have a working change: Team -> Commit, enter a commit description, Commit. Keep in mind that with Git, commits are only local. You can continue to make new commits. When you want to push your tree (of commits) to Github, select Team -> Remote -> Push To Upstream. The changes will be now publicly visible in your GitHub repository.
When you want to submit your changes to dj3500 for testing and review (please do test them thoroughly beforehand, though), create a pull request (from the web interface at https://github.com/YOURUSERNAME/hightail). The pull request model is documented at https://help.github.com/articles/using-pull-requests.
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